Is there a data project return on investment calculation? Can a data project return on investment be calculated at all?

The short answers to both questions are:

  • Direct data project return on investment NO
  • Indirect data project return on investment YES

For brevity, the term “data project” is used in this article to encompass data lakes, lake houses, warehouses, outhouses (and there are plenty), business intelligence and management information.

IMPORTANT: This article adopts a simple view because complexity has no place in making business decisions. A complex business decision equates to a risky business decision and must be avoided. The simple (but not always easy to answer) question is, “Why will a data project solution make us a better and more profitable company?” The answer can be anything except: “because our competitors have one” or “because we’ve been told it’s the way of the future”. Innovate and lead, don’t be a sheep.

What is the value of data?

As beauty is in the eye of the beholder, the same applies to data. The value of data is in the eye of the beholder. Data has perceived value that has no standard accounting value calculation.

Having said that, is there a data project ROI calculation?

Direct data project return on investment

Direct data project return on investment cannot be calculated because a data project is an internal information system.

A data project does not make things that can be sold, nor can it provide a billable service to paying customers.

These two sentences are why you must have a convincing answer to “Why will a data project solution make us a better and more profitable company?” You have to justify why you want to build an additional cost centre. I’ve worked on data projects with budgets up to 15,000,000 Euros, so we aren’t talking about a small investment.

Indirect data project return on investment

We can estimate indirect data project return on investment because the data project provides the organisation with vital information for:

  • recovering from a bad market position (making money)
  • maintaining the organisation’s market position (maintaining cash flow through a difficult period that is showing declining income)
  • improving the organisation’s market position (making money)

The business benefits of a data project are intangible

“If it ain’t broke, don’t fix it.” – Bert Lance

The drive to use a data project solution must be adding value to the organisation. But, let’s be blunt here, adding value is a euphemism for making money; it’s not about an altruistic desire to make employees’ lives easier (although this is a possible side benefit).

Employees use tools as part of their job. Therefore, a data project solution must not be cloning these tools onto a more modern version of the same ones. This may seem common sense, but IT history is strewn with projects that replace previous processes with modern versions of the same functions.

It’s for this reason that a data project solution must add value. It must provide information that will generate business and therefore increase profitability.

For this reason, the benefits are intangible, so before deciding on a data project solution, the business must be convinced that what they are about to spend a lot of money on will genuinely add value.

Every business is unique so identifying “information that will generate business and therefore increase profitability” must be done on a case by case basis.

Never use technology as the driver

Technology advances every day and will continue to do so. Twenty years ago, Artificial Intelligence was science fiction. Today it is embedded in our lives.

Should we use technology as the basis for driving data projects?

No. While it is true that AI is helpful, it is built and administered by humans, and humans are not perfect.

Always use a business case to justify a data project. While business cases are not perfect, they explain the expenditure to achieve a growth or stability objective. Using AI may well be part of the business case, but it is not the reason behind it.

So how do we measure data project return on investment?

The business benefits of data projects are indirect and centred around the ability to make better, faster decisions resulting in cost savings or increased revenue.

Many large organisations, especially those involved in investment banking and international trading, have streaming news feeds shown on their sales and trading staff’s computer screens. The reason being is that if a significant event occurs, they need to react quickly.

A data project provides similarly helpful information so that the organisation can react quickly if necessary or use the information for short-term, medium-term, and long-term strategic planning.

The unleashed power of data projects is their ability to profile at different levels and, when coupled with a big data solution, to react in real-time to immediate events.

The business case estimates the data project’s return on investment by identifying how much it will cost to create and operate and approximating expected financial benefits.

Key areas you should look at when estimating ROI are:

  1. Cost saving – is my data project yielding direct or indirect savings?
  2. Competitive edge – is my data project disrupting or outperforming the competition?
  3. Time to market – is my data project enabling faster product and service delivery?
  4. Increased efficiency – is my data project increasing employee efficiency?
  5. Increased revenue – is my data project increasing our revenue?

The concrete financial proof that a data project is adding value to the organisation should be visible on the income statement.

If (after your data project solution is activated) you don’t see an increase in profitability, your data project return on investment isn’t happening.

Scary? You bet, but this is the real world.

Learn more about data privacy. Take our CPD accredited Data Protection Officer training course.